Image acquisition method, apparatus, system, and electronic device

ABSTRACT

The present disclosure provides image acquisition methods, apparatuses, systems and electronic devices. One image acquisition method includes: acquiring an initial face image of a user by a first image acquisition apparatus; controlling a second image acquisition apparatus to acquire an eye print image of the user according to an acquisition parameter, the acquisition parameter being determined based on the initial face image; and synthesizing the initial face image and the eye print image into a target face image of the user.

CROSS-REFERENCE TO RELATED APPLICATION

This present application is based upon and claims priority to ChineseApplication No. 201810777979.1, filed on Jul. 16, 2018, which isincorporated herein by reference in its entirety.

TECHNICAL FIELD

The present disclosure generally relates to the field of computertechnologies, and in particular, to image acquisition methods,apparatuses, systems and electronic devices.

TECHNICAL BACKGROUND

With the continuous development of pattern recognition, artificialintelligence and other technologies, biometric feature recognitiontechnologies are attracting increasingly more attention. At present,biometric feature recognition mainly includes fingerprint recognition,face recognition, speech recognition, palmprint recognition, eye printrecognition, iris recognition, facial expression recognition, and so on.

In order to improve the accuracy of biometric recognition, sometechnical personnel and research institutions are considering combiningface recognition with eye recognition (such as eye print recognition andiris recognition). The proposed techniques seek to address the problemof inaccurate face recognition for similar faces, such as in cases ofidentical twins. Problems exist with such proposals. For example,ordinary RGB cameras can generally meet the acquisition requirements forface recognition. However, due to issues such as limited resolutions,limited Depth of Field (DoF), and limited Field of View (FoV), ordinaryRGB cameras cannot achieve accurate acquisition of the eye region.Accordingly, there is a need for optimized image acquisition solutionsto improve the accuracy of face recognition.

SUMMARY

In view of the above, embodiments of the specification provide imageacquisition methods, apparatuses, systems and electronic devices. Oneadvantage of the embodiments disclosed herein is to provide optimizedsolutions for face image acquisition.

In one aspect, an image acquisition method comprises: acquiring aninitial face image of a user by a first image acquisition apparatus;controlling a second image acquisition apparatus to acquire an eye printimage of the user according to an acquisition parameter, the acquisitionparameter being determined based on the initial face image; andsynthesizing the initial face image and the eye print image into atarget face image of the user.

In another aspect, an image acquisition apparatus comprises: a firstacquisition unit configured to acquire an initial face image of a userby a first image acquisition apparatus; a second acquisition unitconfigured to control a second image acquisition apparatus to acquire aneye print image of the user according to an acquisition parameter, theacquisition parameter being determined based on the initial face image;and a synthesis unit configured to synthesize the initial face image andthe eye print image into a target face image of the user.

In yet another aspect, an image acquisition system comprises a firstimage acquisition apparatus, a second image acquisition apparatus, acontrol apparatus, and a synthesis apparatus. The first imageacquisition apparatus is configured to acquire an initial face image ofa user. The second image acquisition apparatus is configured to acquirean eye print image of the user. The control apparatus is configured tocontrol the second image acquisition apparatus to acquire the eye printimage of the user according to an acquisition parameter. The synthesisapparatus is configured to synthesize the initial face image and the eyeprint image into a target face image of the user.

In yet another aspect, an electronic device comprises: a processor, anda memory configured to store a set of computer executable instructions.When executed, the executable instructions cause the processor toperform: acquiring an initial face image of a user by a first imageacquisition apparatus; controlling a second image acquisition apparatusto acquire an eye print image of the user according to an acquisitionparameter, the acquisition parameter being determined based on theinitial face image; and synthesizing the initial face image and the eyeprint image into a target face image of the user.

In yet another aspect, a computer-readable storage medium storing one ormore programs is provided. When executed by a processor of an electronicdevice, the one or more programs cause the electronic device to perform:acquiring an initial face image of a user by a first image acquisitionapparatus; controlling a second image acquisition apparatus to acquirean eye print image of the user according to an acquisition parameter,the acquisition parameter being determined based on the initial faceimage; and synthesizing the initial face image and the eye print imageinto a target face image of the user.

The technical solutions provided in the embodiments of thisspecification have at least the following technical advantages. When aface image of a user is acquired, an initial face image of the user canbe acquired by a first image acquisition apparatus. An acquisitionparameter can be determined based on the initial face image. Then asecond image acquisition apparatus can be controlled to acquire an eyeprint image of the user according to the acquisition parameter. Theinitial face image and the eye print image are synthesized into a targetface image of the user. As such, the acquired face image includes theface image of the user as well as an eye region image of the user. Theeye region image is the eye print image of the user. On one hand, theaccuracy of face recognition can be improved. On the other hand, thesecond image acquisition apparatus can be controlled to acquire the eyeprint image of the user based on the initial face image of the user,thereby avoiding the need for the user to adjust his/her own acquisitionangle. User experience can therefore be improved.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings described herein are provided for furthercomprehension of the specification and constitute a part of the presentapplication. The embodiments of the specification and the descriptionthereof are used for illustration purposes, and they do not constituteany improper limitation on the scope of to the specification.

FIG. 1 is a flow chart of an image acquisition method according to anembodiment.

FIG. 2 is a schematic diagram illustrating an image acquisition methodapplied to an actual scenario according to an embodiment.

FIG. 3 is a schematic diagram of an image acquisition apparatusaccording to an embodiment.

FIG. 4 is a schematic diagram of an image acquisition system accordingto an embodiment.

FIG. 5 is a schematic diagram of an electronic device according to anembodiment.

DETAILED DESCRIPTION

Exemplary embodiments are described in detail in the following and areillustrated in the drawings. It is appreciated that the embodimentsdescribed below and illustrated in the drawings are exemplary only. Theydo not constitute any limitations on the scope of the presentdisclosure.

In order to solve the problem that existing face image acquisitionmethods are not optimized enough, an image acquisition method isprovided in the embodiments of this specification. The image acquisitionmethod provided in the embodiments may be executed by, but not limitedto, at least one of user terminals that are configured to perform themethod provided in the embodiments such as mobile phones, tabletcomputers, and wearable devices. Or, the method may also be executed bya client terminal that can perform the method.

In the following description, as an example, the method is described asbeing performed by a mobile terminal. It should be appreciated that themethod being performed by a mobile terminal is only exemplary. In otherembodiments, the method may be performed by other devices.

FIG. 1 is a flow chart of an image acquisition method 100 according toan embodiment. As shown in FIG. 1, the image acquisition method 100includes the following steps 110-130.

In step 110, an initial face image of a user is acquired by a firstimage acquisition apparatus.

As noted in the Technical Background, existing ordinary RGB cameras forface image acquisition can generally meet the acquisition requirementsfor face recognition. However, for acquisition of eye prints in an eyeregion, ordinary RGB cameras may have the following problems. OrdinaryRGB cameras have limited resolutions, which may not deliver highresolution of the acquired eye prints in the eye region. Further,ordinary RGB cameras have a limited DoF, which may not ensure accuratefocusing on the eye region. In addition, ordinary RGB cameras have alimited FoV, which makes it difficult to maintain a wide FoV whilecapturing the eye prints in the eye region and difficult to acquire eyeprints of users of different heights.

Some existing iris imaging techniques perform iris acquisition using asingle camera. Imaging DoF and FoV of the single camera used are bothlimited. Image acquisition of the eye region requires the user to be ina specific position, which affects user experience. In addition, irisacquisition also requires adding an infrared light supplementingcomponent and an infrared filter to an imaging system, which increasescomplexity of the imaging system.

In order to address the above problems, according to the imageacquisition methods provided in an embodiment of this specification, afirst image acquisition apparatus is configured to acquire an initialface image of a user and a second image acquisition apparatus isconfigured to acquire an eye print image of the user. That way,acquisition of a face image and an eye image can be performed at thesame time. The first image acquisition apparatus can acquire the initialface image of the user in different manners. In some embodiments, theinitial face image may be acquired based on a face video stream of theuser acquired by the first image acquisition apparatus in real time.

In step 120, a second image acquisition apparatus is controlled toacquire an eye print image of the user according to a target acquisitionparameter, the target acquisition parameter being determined based onthe initial face image.

As noted above, with the existing techniques, user experience isaffected as the user may need to be in a specific position in order toperform image acquisition of the eye region. According to someembodiments of this specification, a second image acquisition apparatusis controlled to acquire an eye print image of the user according to atarget acquisition parameter. The target acquisition parameter of thesecond image acquisition apparatus can be determined based on theinitial face image. Then the second image acquisition apparatus iscontrolled to acquire the eye print image of the user based on thetarget acquisition parameter. The target acquisition parameter caninclude parameter information such as an acquisition angle and anacquisition height of the second image acquisition apparatus. That way,it is no longer needed for the user to adjust his/her own height orangle multiple times to cooperate with the second image acquisitionapparatus for acquiring an eye print image. User experience cantherefore be improved.

Different users may have different heights and different pupillarydistances. In order to ensure that the second image acquisitionapparatus can acquire a clear eye print image, the determining a targetacquisition parameter of the second image acquisition apparatus based onthe initial face image can include the following procedures. First,spatial location information of the user's eye region can be determinedbased on the initial face image of the user. For example, key points canbe located based on the initial face image of the user to facilitatedetermining the spatial location information of the user's eye region. Atarget acquisition parameter of the second image acquisition apparatuscan be determined based on the spatial location information of theuser's eye region. For example, a target acquisition parameter can be anoptimal acquisition angle or acquisition height. The spatial locationinformation of the user's eye region can include pupil center locationinformation of the user's eyes.

In an embodiment, in order to ensure that the second image acquisitionapparatus can acquire a sufficiently clear eye print image, thecontrolling a second image acquisition apparatus to acquire an eye printimage of the user according to a target acquisition parameter mayinclude the following procedures. First, the second image acquisitionapparatus can be controlled to acquire an eye region image of the useraccording to the target acquisition parameter. The eye region image ofthe user can then be segmented by using a full convolutional depthneural network, to acquire an eye print image of which the sharpnessmeets a preset condition. As the eye region image of the user issegmented by the full convolutional depth neural network, the quality ofthe acquired eye print image can be quickly evaluated. That way, it canhelp the second image acquisition apparatus to focus, and to obtain asufficiently clear eye print image.

In some embodiments, the first image acquisition apparatus is configuredto acquire a face image of the user, the second image acquisitionapparatus is configured to acquire an eye print image of the user. Thefirst image acquisition apparatus and the second image acquisitionapparatus can have different FoV requirements. In order to meet thedifferent acquisition requirements, a camera with a large FoV may beselected for the first image acquisition apparatus, and a camera with asmall FoV may be selected for the second image acquisition apparatus.That is, the FoV of the first image acquisition apparatus can be greaterthan that of the second image acquisition apparatus. For example, theFoV of the first image acquisition apparatus can be greater than orequal to 45° *100°; and the FoV of the second image acquisitionapparatus can be greater than or equal to 50 mm*140 mm.

In the forgoing example, other parameters of the first image acquisitionapparatus and the second image acquisition apparatus can be as follows:a spatial resolution of the first image acquisition apparatus can begreater than or equal to 2 mm, an imaging distance range can be 500 mmto 1000 mm, and an image frame rate can be greater than or equal to 15fps. A spatial resolution of the second image acquisition apparatus canbe no less than 3-5 line pairs/mm.

As gimbals provide relatively high accuracy and are easy to control, thesecond image acquisition apparatus can be controlled by a gimbal, e.g.,a steering gimbal, a servo gimbal, etc., to adjust acquisitionparameters such as an image acquisition angle, according to anembodiment. The step of controlling a second image acquisition apparatusto acquire an eye print image of the user according to a targetacquisition parameter may include: controlling the second imageacquisition apparatus by using a gimbal to acquire the eye print imageof the user according to the target acquisition parameter.

In an embodiment, a lens of the second image acquisition apparatus maybe an optical zoom lens or a prime lens. If the lens of the second imageacquisition apparatus is an optical zoom lens, the optical zoom lens canensure a consistent acquisition resolution for acquisition of the eyeprint image at different distances. If the lens of the second imageacquisition apparatus is a prime lens, digital zoom can be used tofacilitate adjustment of a lens focal length to obtain a clear eye printimage. Using digital zoom with the prime lens may reduce the cost of thewhole image acquisition system, but the sharpness of the eye print imageacquired may be affected compared with that of the eye print imageacquired by the optical zoom lens. In addition, in order to ensure thatthe second image acquisition apparatus can acquire an eye print image ofwhich the sharpness meets a preset condition, no matter which lens isused by the second image acquisition apparatus, the DoF of the lens canbe greater than or equal to 2 cm.

FIG. 2 is a schematic diagram illustrating an image acquisition methodapplied to an actual scenario 200 according to one embodiment. Thediagram in FIG. 2 illustrates two aspects of the application scenario200: a software algorithm 210 and an imaging system 220. The imagingsystem 220 includes a camera 221, which is a face acquisition camerawith a large FoV; a camera 222, which is an eye print acquisition camerawith a small FoV; and a gimbal 223, e.g., a steering gimbal, a servogimbal, etc., configured to control an acquisition parameter of thecamera 222. It is appreciated that the camera 221 can serve as the firstimage acquisition apparatus described above, and the camera 222 canserve as the second image acquisition apparatus described above and canbe a camera using an optical zoom lens.

The software algorithm 210 mainly includes face detection algorithm(s),eye detection algorithm(s), and control algorithm(s), which can bestored in a control chip 211 or stored in an upper computer 212.

As an example, the process of acquiring an initial face image and an eyeprint image of a user in the scenario illustrated in FIG. 2 can include:acquiring a face video stream of the user by the camera 221; acquiringthe face video stream by the control chip 211 or the upper computer 212;acquiring an initial face image by face detection, acquiring pupilcenter location information of two eyes of the user by key pointlocating and eye detection, and determining a target acquisitionparameter of the camera 222 based on the location information; sendingthe target acquisition parameter to the gimbal 223; and controlling thecamera 222, by the gimbal 223 after the target acquisition parameter isreceived, to acquire the eye print image of the user according to thetarget acquisition parameter.

Referring back to FIG. 1, in step 130, the initial face image and theeye print image are synthesized into a target face image of the user.

After the initial face image of the user is acquired by the first imageacquisition apparatus and the eye print image of the user is acquired bythe second image acquisition apparatus respectively, the initial faceimage and the eye print image can be synthesized into a target faceimage of the user. When performing identity verification for the user,identity verification can be carried out using a combination of the faceimage and the eye print image. Eye print image recognition can be usedto distinguish people's identity according to arrangements of bloodvessels in the white area of the human eye. Every person has a uniqueeye print. Even twins with a high facial similarity have differentarrangements of blood vessels in their eye prints. Therefore, identityverification carried out using a combination of the face image and theeye print image can be more accurate.

According to the above-described embodiments, an initial face image ofthe user can be acquired by a first image acquisition apparatus, basedon which a target acquisition parameter can be determined. Then a secondimage acquisition apparatus can be controlled to acquire an eye printimage of the user according to a target acquisition parameter. Theinitial face image and the eye print image can be synthesized into atarget face image of the user. As such, the acquired face image includesthe face image of the user and an eye region image of the user, which isthe eye print image of the user. On one hand, the accuracy of facerecognition can be improved. On the other hand, the second imageacquisition apparatus can also be controlled to acquire the eye printimage of the user based on the initial face image of the user, thusavoiding the situation that the user needs to adjust his/her ownacquisition angle. User experience can therefore be improved.

FIG. 3 is a schematic diagram of an image acquisition apparatus 300according to an embodiment. Referring to FIG. 3, the image acquisitionapparatus 300 can include a first acquisition unit 310, a secondacquisition unit 320, and a synthesis unit 330.

The first acquisition unit 310 is configured to acquire an initial faceimage of a user by a first image acquisition apparatus.

The second acquisition unit 320 is configured to control a second imageacquisition apparatus to acquire an eye print image of the useraccording to a target acquisition parameter, the target acquisitionparameter being determined based on the initial face image.

The synthesis unit 330 is configured to synthesize the initial faceimage and the eye print image into a target face image of the user.

With the image acquisition apparatus 300, the first acquisition unit 310can acquire an initial face image of the user by a first imageacquisition apparatus. A target acquisition parameter can be determinedbased on the initial face image. The second acquisition unit 320controls a second image acquisition apparatus to acquire an eye printimage of the user according to the target acquisition parameter.Finally, the initial face image and the eye print image are synthesizedinto a target face image of the user by the synthesis unit 330. As such,the acquired face image includes the face image of the user and an eyeregion image of the user, which is the eye print image of the user. Onone hand, the accuracy of face recognition can be improved. On the otherhand, the second image acquisition apparatus can be controlled toacquire the eye print image of the user based on the initial face imageof the user, thus avoiding the situation that the user needs to adjusthis/her own acquisition angle. User experience can therefore beimproved.

In an embodiment, the second acquisition unit 320 is configured to:determine a target acquisition parameter of the second image acquisitionapparatus based on the initial face image; and control the second imageacquisition apparatus to acquire the eye print image of the user basedon the target acquisition parameter.

In an embodiment, the second acquisition unit 320 is configured to:determine eye region spatial location information of the user based onthe initial face image of the user; and determine the target acquisitionparameter of the second image acquisition apparatus based on the eyeregion spatial location information of the user.

In an embodiment, the second acquisition unit 320 is configured to:control the second image acquisition apparatus to acquire an eye regionimage of the user according to the target acquisition parameter; andsegment the eye region image of the user by a full convolutional depthneural network to acquire an eye print image of which the sharpnessmeets a preset condition.

In an embodiment, an FoV of the first image acquisition apparatus isgreater than that of the second image acquisition apparatus.

In an embodiment, the FoV of the first image acquisition apparatus isgreater than or equal to 45° *100°; and the FoV of the second imageacquisition apparatus is greater than or equal to 50 mm*140 mm.

In an embodiment, the second acquisition unit 320 is configured to:control the second image acquisition apparatus by using a gimbal, e.g.,a steering gimbal, a servo gimbal, etc., to acquire the eye print imageof the user according to the target acquisition parameter.

In an embodiment, a lens of the second image acquisition apparatus is anoptical zoom lens or a prime lens.

In an implementation manner, the DoF of the second image acquisitionapparatus is greater than or equal to 2 cm.

In an embodiment, the eye region spatial location information of theuser includes pupil center location information of two eyes of the user.

It is appreciated that the image acquisition apparatus 300 can implementthe methods described above in connection with FIG. 1 and FIG. 2.Reference can be made to the description above, which is not repeatedherein.

FIG. 4 is a schematic diagram of an image acquisition system 400according to an embodiment of this specification. Referring to FIG. 4,the image acquisition system 400 can include a first image acquisitionapparatus 410, a second image acquisition apparatus 420, a controlapparatus 430, and a synthesis apparatus 440.

The first image acquisition apparatus 410 is configured to acquire aninitial face image of a user.

The second image acquisition apparatus 420 is configured to acquire aneye print image of the user.

The control apparatus 430 is configured to control the second imageacquisition apparatus 420 to acquire the eye print image of the useraccording to a target acquisition parameter.

The synthesis apparatus 440 is configured to synthesize the initial faceimage and the eye print image into a target face image of the user.

In an embodiment, the control apparatus 430 is configured to: determinea target acquisition parameter of the second image acquisition apparatusbased on the initial face image; and control the second imageacquisition apparatus to acquire the eye print image of the user basedon the target acquisition parameter.

In an embodiment, the control apparatus 430 is configured to: determineeye region spatial location information of the user based on the initialface image of the user; and determine the target acquisition parameterof the second image acquisition apparatus based on the eye regionspatial location information of the user.

In an embodiment, the control apparatus 430 is configured to: controlthe second image acquisition apparatus to acquire an eye region image ofthe user according to the target acquisition parameter; and segment theeye region image of the user by a full convolutional depth neuralnetwork to acquire an eye print image of which the sharpness meets apreset condition.

In an embodiment, an FoV of the first image acquisition apparatus 410 isgreater than that of the second image acquisition apparatus 420.

In an embodiment, the FoV of the first image acquisition apparatus 410is greater than or equal to 45° *100°; and the FoV of the second imageacquisition apparatus 420 is greater than or equal to 50 mm*140 mm.

In an embodiment, the control apparatus 430 is configured to: controlthe second image acquisition apparatus by using a gimbal, e.g., asteering gimbal, a servo gimbal, etc., to acquire the eye print image ofthe user according to the target acquisition parameter.

In an embodiment, a lens of the second image acquisition apparatus 420is an optical zoom lens or a prime lens.

In an embodiment, the DoF of the second image acquisition apparatus 420is greater than or equal to 2 cm.

In an embodiment, the eye region spatial location information of theuser includes pupil center location information of two eyes of the user.

It is appreciated that the image acquisition system 400 can implementthe methods described above in connection with FIG. 1 and FIG. 2.Reference can be made to the description above, which is not repeatedherein.

FIG. 5 is a schematic diagram of an electronic device 500 according toan embodiment. Referring to FIG. 5, the electronic device 500 includes aprocessor 510, an internal bus 520, a network interface 530, and amemory, such as an internal memory 540 or a non-volatile memory 550. Theinternal memory 540 may include a memory such as a high-speedRandom-Access Memory (RAM). The non-volatile memory 550 may include, forexample, one magnetic disk memory. It is appreciated that the electronicdevice 500 may further include other hardware components, which are notlimited herein.

The processor 510, the network interface 530, and the memory may beinterconnected through the internal bus 520. The internal bus 520 may bean Industry Standard Architecture (ISA) bus, a Peripheral ComponentInterconnect (PCI) bus, an Extended Industry Standard Architecture(EISA) bus, or the like. The internal bus 520 may further be classifiedinto an address bus, a data bus, a control bus, and the like. It isappreciated that the electronic device 500 may include more than one busand may include different types of buses.

The internal memory 540 and the non-volatile memory 550 are configuredto store a program. The program may include program codes orcomputer-executable instructions that can be executed the by processor510. For example, the processor 510 can read the program codes orcomputer-executable instructions to perform the following procedures:acquiring an initial face image of a user by a first image acquisitionapparatus; controlling a second image acquisition apparatus to acquirean eye print image of the user according to a target acquisitionparameter, the target acquisition parameter being determined based onthe initial face image; and synthesizing the initial face image and theeye print image into a target face image of the user.

It is appreciated that the processor 510 may further executeinstructions to perform methods described above in connection withFIG. 1. The processor 510 may be an integrated circuit chip having asignal processing capability. In the process of implementation, varioussteps of the above described methods may be performed by an integratedlogic circuit of hardware in the processor, by executing correspondinginstructions in the form of software. The processor 510 may be ageneral-purpose processor, such as a Central Processing Unit (CPU), aNetwork Processor (NP), etc. The processor 510 may also be a DigitalSignal Processor (DSP), an Application Specific Integrated Circuit(ASIC), a Field-Programmable Gate Array (FPGA) or another programmablelogic device, a discrete gate or transistor logic device, or a discretehardware component.

Further, the general-purpose processor may be a microprocessor, or anyother types of processors. The steps of the methods described above maybe directly performed by a hardware decoding processor or may beperformed by a combination of hardware and software modules in thedecoding processor. The software module can be located in a storagemedium, such as a random-access memory, a flash memory, a read-onlymemory, a programmable read-only memory or an electrically erasableprogrammable memory, a register, and the like. The storage medium can belocated in the memory, and the processor can read the information in thememory and perform the steps of the above-described method embodiments.Further, it is appreciated that in addition to the softwareimplementation manner, the electronic device 500 may also be implementedin other implementation manners, such as in the form of logic devices ora combination of software and hardware.

The computer readable medium can include non-volatile and volatile mediaas well as movable and non-movable media, which can implementinformation storage by means of various techniques. The information maybe a computer readable instruction, a data structure, and a module of aprogram or other data. Examples of the storage medium of a computerinclude, but is not limited to, a phase change memory (PRAM), a staticrandom access memory (SRAM), a dynamic random access memory (DRAM),other types of RAMs, a ROM, an electrically erasable programmableread-only memory (EEPROM), a flash memory or other memory technologies,a compact disk read-only memory (CD-ROM), a digital versatile disc (DVD)or other optical storages, a cassette tape, a magnetic tape/magneticdisk storage or other magnetic storage devices, or any othernon-transmission medium, and can be used to store information accessibleto a computing device. Further, as used in this specification, thecomputer readable medium does not include transitory media, such as amodulated data signal or a carrier.

Each of the above described units may be implemented as software, orhardware, or a combination of software and hardware. For example, eachof the above described units may be implemented using a processorexecuting instructions stored in a memory. Also, for example, each ofthe above described units may be implemented with one or moreapplication specific integrated circuits (ASICs), digital signalprocessors (DSPs), digital signal processing devices (DSPDs),programmable logic devices (PLDs), field programmable gate arrays(FPGAs), controllers, micro-controllers, microprocessors, or otherelectronic components, for performing the above described methods.

The systems, apparatuses, modules or units illustrated in the aboveembodiments may be implemented by a computer chip or a computing entity,or by a product having a certain function. A typical implementationdevice can be a computer. For example, the computer may be a personalcomputer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigationdevice, an email device, a game console, a tablet computer, a wearabledevice, or a combination of any of these devices.

It is appreciated that the terms “include,” “comprise” or any othervariations thereof are intended to cover non-exclusive inclusion. Thatis, a process, method, article or device including a series of elementsmay not only include the elements, but also include other elements notexpressly listed, or further include elements inherent to the process,method, article or device. In the absence of specific limitations, anelement defined by “including a/an . . . ” does not exclude that theprocess, method, article or device includes a plurality of identicalelements, or other elements.

The above description provides only exemplary embodiments of thespecification and is not intended to limit the specification. Variouschanges and modifications can be made to the embodiments by thoseskilled in the art, consistent with the specification. Anymodifications, equivalent substitutions, improvements, etc. made withinthe spirit and scope of the specification shall all fall within thescope defined in the appended claims.

1. An image acquisition method, comprising: acquiring an initial faceimage of a user by a first image acquisition apparatus; controlling asecond image acquisition apparatus to acquire an eye print image of theuser according to an acquisition parameter, the acquisition parameterbeing determined based on the initial face image; and synthesizing theinitial face image and the eye print image into a target face image ofthe user.
 2. The method of claim 1, wherein the controlling a secondimage acquisition apparatus to acquire an eye print image of the usercomprises: determining the acquisition parameter based on the initialface image of the user; and controlling the second image acquisitionapparatus to acquire the eye print image of the user based on theacquisition parameter.
 3. The method of claim 2, wherein the determiningthe acquisition parameter based on the initial face image of the usercomprises: determining eye region spatial location information of theuser based on the initial face image of the user; and determining theacquisition parameter based on the eye region spatial locationinformation of the user.
 4. The method of claim 1, wherein thecontrolling a second image acquisition apparatus to acquire an eye printimage of the user comprises: controlling the second image acquisitionapparatus to acquire an eye region image of the user according to theacquisition parameter; and segmenting the eye region image using a fullconvolutional depth neural network to acquire the eye print image, asharpness of the eye print image meeting a preset condition.
 5. Themethod of claim 1, wherein: a Field of View (FoV) of the first imageacquisition apparatus is greater than an FoV of the second imageacquisition apparatus.
 6. The method of claim 5, wherein: the FoV of thefirst image acquisition apparatus is greater than or equal to 45° *100°;and the FoV of the second image acquisition apparatus is greater than orequal to 50 mm*140 mm.
 7. The method of claim 1, wherein the controllinga second image acquisition apparatus to acquire an eye print image ofthe user comprises: controlling the second image acquisition apparatusby using a gimbal to acquire the eye print image of the user accordingto the acquisition parameter.
 8. The method of claim 1, wherein a lensof the second image acquisition apparatus is one of an optical zoom lensor a prime lens.
 9. The method of claim 1, wherein a Depth of Field(DoF) of the second image acquisition apparatus is greater than or equalto 2 cm.
 10. The method of claim 3, wherein the eye spatial locationinformation of the user comprises pupil center location information oftwo eyes of the user.
 11. An electronic device, comprising: a memorystoring instructions; and a processor configured to execute theinstructions to: acquire an initial face image of a user by a firstimage acquisition apparatus; control a second image acquisitionapparatus to acquire an eye print image of the user according to anacquisition parameter, the acquisition parameter being determined basedon the initial face image; and synthesize the initial face image and theeye print image into a target face image of the user.
 12. The electronicdevice of claim 11, wherein the processor is further configured toexecute the instructions to: determine the acquisition parameter basedon the initial face image of the user; and control the second imageacquisition apparatus to acquire the eye print image of the user basedon the acquisition parameter.
 13. The electronic device of claim 12,wherein the processor is further configured to execute the instructionsto: determine eye region spatial location information of the user basedon the initial face image of the user; and determine the acquisitionparameter based on the eye region spatial location information of theuser.
 14. The electronic device of claim 11, wherein the processor isfurther configured to execute the instructions to: control the secondimage acquisition apparatus to acquire an eye region image of the useraccording to the acquisition parameter; and segment the eye region imageusing a full convolutional depth neural network to acquire the eye printimage, a sharpness of the eye print image meeting a preset condition.15. The electronic device of claim 11, wherein: a Field of View (FoV) ofthe first image acquisition apparatus is greater than an FoV of thesecond image acquisition apparatus.
 16. The electronic device of claim15, wherein: the FoV of the first image acquisition apparatus is greaterthan or equal to 45° *100°; and the FoV of the second image acquisitionapparatus is greater than or equal to 50 mm*140 mm.
 17. The electronicdevice of claim 11, the processor is further configured to execute theinstructions to: control the second image acquisition apparatus by usinga gimbal to acquire the eye print image of the user according to theacquisition parameter.
 18. The electronic device of claim 11, wherein alens of the second image acquisition apparatus is one of an optical zoomlens or a prime lens.
 19. The electronic device of claim 11, wherein aDepth of Field (DoF) of the second image acquisition apparatus isgreater than or equal to 2 cm.
 20. A non-transitory computer-readablemedium storing instructions that, when executed by a processor of adevice, cause the device to perform an image acquisition method, themethod comprising: acquiring an initial face image of a user by a firstimage acquisition apparatus; controlling a second image acquisitionapparatus to acquire an eye print image of the user according to anacquisition parameter, the acquisition parameter being determined basedon the initial face image; and synthesizing the initial face image andthe eye print image into a target face image of the user.